An Efficient Provable Data Possession Scheme with Data Dynamics

Li, Chaoling; Chen, Yue; Peng-xu, Tan; Yang, Gang

doi:10.1109/csss.2012.182

Cited by 10 publications

(7 citation statements)

References 8 publications

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“…C. Li et al proposed PDP techniques to insert and edit a new data block to the stored data [13]. This generates a table based on the index of the location index and the physical location of the logical block stored in the block.…”

Section: Verification-process In Pdpmentioning

confidence: 99%

An Efficient Provable Data Possession Scheme based on Counting Bloom Filter for Dynamic Data in the Cloud Storage

Jung¹,

Jeong

2016

IJMUE

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Cloud services have become a trend, because many companies are supplying various cloud services that reflect the needs of users. However, as cloud services increase, security problems, such as saved data spills and data modulation, also increase. This paper focuses on the problem of data integrity. A PDP (Provable Data Possession) scheme has the disadvantage of time overheads, because dynamic data needs additional processing time. To solve the problem, this paper examines the use of a Counting Bloom Filter for updating data. This technique is more efficient than using PDP when changing part of the data in a simulation. The result is more effective if the saved data changes part of the dynamic data.

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Section: Verification-process In Pdpmentioning

confidence: 99%

An Efficient Provable Data Possession Scheme based on Counting Bloom Filter for Dynamic Data in the Cloud Storage

Jung¹,

Jeong

2016

IJMUE

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“…Overall indicators to measure the International Conference on Mechatronics, Electronic, Industrial and Control Engineering (MEIC 2014) merits of a scheme mainly include: computational overhead, storage and communication cost, whether to support the dynamic operation, recoverability, check number, public verification and so on. The following scheme of [4][5][6][7][8][9][10][11][12][13][14][15][16] from above several aspects to compared, as shown in table1. [4][5][6][7][8][9][10][11][12][13][14][15][16]…”

Section: Comparison Of Programs On Data Possession Provabilitymentioning

confidence: 99%

Research of Data Possession Provability Proving on Cloud Computing

Du¹,

Han²,

Bi³

et al. 2014

Proceedings of the 2014 International Conference on Mechatronics, Electronic, Industrial and Control Engineering

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With the rapid development of cloud computing, more and more data to be stored in the cloud storage servers. Cloud storage as a new type of storage services, with high scalability, high reliability, low cost, can be accessed anytime and anywhere features, provides a new model for mass data storage management. However, due to data are outsourcing to a cloud services provider, users are actually relinquishing the ultimate control over the fate of their data, so it faces many challenges. Data possession provability allows cloud users to verify whether their data are still integrally, validly and correctly preserved in Cloud Storage system, and whether they can obtain the data at anytime, anywhere. It is a challenging research problem of cloud storage security. This paper concluded data persistence proving model from some aspects such as general encryption scheme to the data, homomorphic encryption scheme, third-party audit (TPA) and so on. This paper discussed and summarized the existing data persistence proving schemes and models, and concluded a general model based on data persistence proving model of TPA (third-party audits).

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“…However, the efficiency of update operations remains in question. Li et al proposed the support of block insertions using SN-BN tables [6], which match the logical indices of blocks with their actual positions. Though the support for insertion in these dynamic PDP schemes is much like the add operation on file groups in our scheme, we emphasize that the overhead of preserving such complicated data structures is nonnegligible.…”

Section: Related Workmentioning

confidence: 99%

“…Though numerous PDP schemes have been proposed in recent years [2]- [6], [12]- [14], there is still considerable room of improvement to apply these theoretical schemes to actual cloud storage environments. Two issues seriously affect the practicality of PDP schemes.…”

Section: Introductionmentioning

confidence: 99%

“…First, data stored in the cloud is massive and dynamic in nature, making the original PDP scheme [1] for a single static file unsuitable. Later schemes that support dynamic data updates [2]- [6] often introduce complicated authenticated data structures, which add significant overhead to the schemes. Moreover, when naively extending these single-file schemes to apply to a large number of files, which is a common scenario in cloud storage, the overhead becomes prohibitively larger.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Data Possession Auditing for Real-World Cloud Storage Environments

Xiao

Yang

Liu

et al. 2015

IEICE Trans. Inf. & Syst.

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SUMMARYProvable Data Possession (PDP) schemes enable users to efficiently check the integrity of their data in the cloud. Support for massive and dynamic sets of data and adaptability to third-party auditing are two key factors that affect the practicality of existing PDP schemes. We propose a secure and efficient PDP system called IDPA-MF-PDP, by exploiting the characteristics of real-world cloud storage environments. The cost of auditing massive and dynamic sets of data is dramatically reduced by utilizing a multiple-file PDP scheme (MF-PDP), based on the data update patterns of cloud storage. Deployment and operational costs of third-party auditing and information leakage risks are reduced by an auditing framework based on integrated data possession auditors (DPAs), instantiated by trusted hardware and tamper-evident audit logs. The interaction protocols between the user, the cloud server, and the DPA integrate MF-PDP with the auditing framework. Analytical and experimental results demonstrate that IDPA-MF-PDP provides the same level of security as the original PDP scheme while reducing computation and communication overhead on the DPA, from linear the size of data to near constant. The performance of the system is bounded by disk I/O capacity. key words: provable data possession, third-party audit, tamper-evident audit logs, trusted hardware

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An Efficient Provable Data Possession Scheme with Data Dynamics

Cited by 10 publications

References 8 publications

An Efficient Provable Data Possession Scheme based on Counting Bloom Filter for Dynamic Data in the Cloud Storage

An Efficient Provable Data Possession Scheme based on Counting Bloom Filter for Dynamic Data in the Cloud Storage

Research of Data Possession Provability Proving on Cloud Computing

Efficient Data Possession Auditing for Real-World Cloud Storage Environments

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